PROJECT SUMMARY Given the worldwide scope of the HIV/AIDS epidemic, efficient provision of therapy and the accompanying policy and resource-allocation decisions necessary, likewise have a worldwide scope. One of the components of this response is the accumulation of information and data to support evidence-based policy and decision making at the national and international level. To aid in the coordination of the international response to the HIV/AIDS epidemic, the Joint United Nations Programme on HIV/AIDS (UNAIDS) has undertaken a major initiative to use data from all relevant sources to derive estimates of HIV prevalence in adults and children around the world. These data inform decision and policy-making and help allocation of human and financial resources to combat HIV/AIDS. At the core of this effort is the SPECTRUM model, which generates estimates and projections for every country worldwide and helps to assess the impact of targets such as 90-90-90 and guidelines like universal test and treat. Over the past decade, the International Epidemiology Databases to Evaluate AIDS (IeDEA) worldwide collaboration has developed a close relationship with UNAIDS, providing programmatic data as inputs to the SPECTRUM model. IeDEA and particularly our group (the East Africa IeDEA Regional Consortium), has developed statistical methods to address problems in estimates of mortality and patient retention based on data collected as part of routine clinical care, which stem from unreported mortality in patients lost to programs. We have shown how ascertaining vital status and treatment access on a sample of patients lost to care, who were subsequently traced in the community, we can statistically adjust estimates of mortality and patient retention for an entire program cohort. These methods will be extended to multi-state models of the entire HIV cascade of care, from enrollment into care and antiretroviral treatment (ART) initiation to death, and used to provide rigorous, data-driven inputs to SPECTRUM and other mathematical models (Specific Aim 1). To develop truly global estimates, even in settings where patient tracing is not available, we will extend our methodology to borrow from the experience of programs with available tracing data and, using the clinical data at a new setting, provide adjusted estimates of mortality and patient retention in programs with no tracing data (Specific Aim 2). In this manner, a hitherto unavailable global picture of HIV care and treatment in the post-ART-scale-up world and in the era of Universal Test and Treat will emerge.